Terry Zhuo
test leaderboard+execution
0ee99b8
raw
history blame
6.98 kB
import gradio as gr
import subprocess
import sys
import os
import threading
import time
import uuid
import glob
import shutil
from pathlib import Path
default_command = "bigcodebench.evaluate"
is_running = False
def generate_command(
jsonl_file, split, subset, parallel,
min_time_limit, max_as_limit, max_data_limit, max_stack_limit,
check_gt_only, no_gt
):
command = [default_command]
if jsonl_file is not None:
# Copy the uploaded file to the current directory
local_filename = os.path.basename(jsonl_file.name)
shutil.copy(jsonl_file.name, local_filename)
command.extend(["--samples", local_filename])
command.extend(["--split", split, "--subset", subset])
if parallel is not None and parallel != 0:
command.extend(["--parallel", str(int(parallel))])
command.extend([
"--min-time-limit", str(min_time_limit),
"--max-as-limit", str(int(max_as_limit)),
"--max-data-limit", str(int(max_data_limit)),
"--max-stack-limit", str(int(max_stack_limit))
])
if check_gt_only:
command.append("--check-gt-only")
if no_gt:
command.append("--no-gt")
return " ".join(command)
def cleanup_previous_files(jsonl_file):
if jsonl_file is not None:
file_list = ['Dockerfile', 'app.py', 'README.md', os.path.basename(jsonl_file.name), "__pycache__"]
else:
file_list = ['Dockerfile', 'app.py', 'README.md', "__pycache__"]
for file in glob.glob("*"):
try:
if file not in file_list:
os.remove(file)
except Exception as e:
print(f"Error during cleanup of {file}: {e}")
def find_result_file():
json_files = glob.glob("*.json")
if json_files:
return max(json_files, key=os.path.getmtime)
return None
def run_bigcodebench(command):
global is_running
if is_running:
yield "A command is already running. Please wait for it to finish.\n"
return
is_running = True
try:
yield f"Executing command: {command}\n"
process = subprocess.Popen(command.split(), stdout=subprocess.PIPE, stderr=subprocess.STDOUT, universal_newlines=True)
def kill_process():
if process.poll() is None: # If the process is still running
process.terminate()
is_running = False
yield "Process terminated after 12 minutes timeout.\n"
# Start a timer to kill the process after 12 minutes
timer = threading.Timer(720, kill_process)
timer.start()
for line in process.stdout:
yield line
# process.wait()
timer.cancel()
if process.returncode != 0:
yield f"Error: Command exited with status {process.returncode}\n"
yield "Evaluation completed.\n"
result_file = find_result_file()
if result_file:
yield f"Result file found: {result_file}\n"
else:
yield "No result file found.\n"
finally:
is_running = False
def stream_logs(command, jsonl_file=None):
global is_running
if is_running:
yield "A command is already running. Please wait for it to finish.\n"
return
cleanup_previous_files(jsonl_file)
yield "Cleaned up previous files.\n"
log_content = []
for log_line in run_bigcodebench(command):
log_content.append(log_line)
yield "".join(log_content)
# with gr.Blocks() as demo:
# gr.Markdown("# BigCodeBench Evaluator")
# with gr.Row():
# jsonl_file = gr.File(label="Upload JSONL file", file_types=[".jsonl"])
# split = gr.Dropdown(choices=["complete", "instruct"], label="Split", value="complete")
# subset = gr.Dropdown(choices=["hard", "full"], label="Subset", value="hard")
# with gr.Row():
# parallel = gr.Number(label="Parallel (optional)", precision=0)
# min_time_limit = gr.Number(label="Min Time Limit", value=1, precision=1)
# max_as_limit = gr.Number(label="Max AS Limit", value=25*1024, precision=0)
# with gr.Row():
# max_data_limit = gr.Number(label="Max Data Limit", value=25*1024, precision=0)
# max_stack_limit = gr.Number(label="Max Stack Limit", value=10, precision=0)
# check_gt_only = gr.Checkbox(label="Check GT Only")
# no_gt = gr.Checkbox(label="No GT")
# command_output = gr.Textbox(label="Command", value=default_command, interactive=False)
# with gr.Row():
# submit_btn = gr.Button("Run Evaluation")
# download_btn = gr.DownloadButton(label="Download Result")
# log_output = gr.Textbox(label="Execution Logs", lines=20)
# input_components = [
# jsonl_file, split, subset, parallel,
# min_time_limit, max_as_limit, max_data_limit, max_stack_limit,
# check_gt_only, no_gt
# ]
# for component in input_components:
# component.change(generate_command, inputs=input_components, outputs=command_output)
# def start_evaluation(command, jsonl_file, subset, split):
# extra = subset + "_" if subset != "full" else ""
# if jsonl_file is not None:
# result_path = os.path.basename(jsonl_file.name).replace(".jsonl", f"_{extra}eval_results.json")
# else:
# result_path = None
# for log in stream_logs(command, jsonl_file):
# if jsonl_file is not None:
# yield log, gr.update(value=result_path, label=result_path), gr.update()
# else:
# yield log, gr.update(), gr.update()
# result_file = find_result_file()
# if result_file:
# return gr.update(label="Evaluation completed. Result file found."), gr.update(value=result_file)
# # gr.Button(visible=False)#,
# # gr.DownloadButton(label="Download Result", value=result_file, visible=True))
# else:
# return gr.update(label="Evaluation completed. No result file found."), gr.update(value=result_path)
# # gr.Button("Run Evaluation", visible=True),
# # gr.DownloadButton(visible=False))
# submit_btn.click(start_evaluation,
# inputs=[command_output, jsonl_file, subset, split],
# outputs=[log_output, download_btn])
# REPO_ID = "bigcode/bigcodebench-evaluator"
# HF_TOKEN = os.environ.get("HF_TOKEN", None)
# API = HfApi(token=HF_TOKEN)
# def restart_space():
# API.restart_space(repo_id=REPO_ID, token=HF_TOKEN)
# demo.queue(max_size=300).launch(share=True, server_name="0.0.0.0", server_port=7860)
# scheduler = BackgroundScheduler()
# scheduler.add_job(restart_space, "interval", hours=3) # restarted every 3h as backup in case automatic updates are not working
# scheduler.start()